Patient monitoring systems and methods

ABSTRACT

Techniques disclosed herein relate to monitoring changes in conditions of multiple individuals in areas. In some embodiments, a patient monitoring queue may be established ( 504 ) that includes a plurality of patients in an area ( 104, 304 ) such as a waiting room. The area may be capturable by vital sign acquisition camera(s) ( 276. 376, 476 ) mounted in or near the area. Updated vital sign(s) may be unobtrusively acquired ( 510 ) by the vital sign acquisition camera(s) from a given patient selected ( 506 ) from the patient monitoring queue. Based on the updated vital sign(s) and prior vital signs acquired previously from the given patient, deterioration of the given patient may be detected ( 512 ). Output may be provided ( 514 ) alerting medical personnel of the deterioration of the given patient.

CROSS-REFERENCE TO PRIOR APPLICATIONS

This application is the U.S. National Phase application under 35 U.S.C.§ 371 of International Application No. PCT/EP2017/074588, filed on Sep.28, 2017, which claims the benefit of Provisional Application Ser. No.62/404,94, filed Oct. 5, 2016. These applications are herebyincorporated by reference herein, for all purposes.

TECHNICAL FIELD

The present disclosure is directed generally to health care. Moreparticularly, but not exclusively, various methods and apparatusdisclosed herein relate to monitoring changes in conditions of multipleindividuals such as patients in areas such as waiting rooms.

BACKGROUND

When patients visit the hospital, they typically are triaged todetermine various information about the patients, such as their names,ages, heights, weights, vital signs, reasons for visiting, and othersimilar information. Once triaged, the patients are sent to an area suchas a waiting room to wait for hospital resources such as physicians tobecome available to examine and/or treat the patients. Wait times forthe patients may be significant depending on availability of hospitalresources. It is not uncommon for patients to deteriorate while waiting,and medical personnel may not always become aware of the deteriorationin a timely fashion.

SUMMARY

The present disclosure is directed to methods, systems, and apparatusfor monitoring changes in conditions of multiple individuals such aspatients in an area such as waiting rooms. For example, a plurality oftriaged patients may wait in a waiting room until they can be seen by anemergency room (“ER”) physician. The patients may be included in apatient monitoring queue (also referred to simply as a “patient queue”)that is ordered or ranked, for instance, based on a measure of acuityassociated with each patient (referred to herein as a “patient acuitymeasure”) that is determined based on information obtained/acquired fromthe patient by a triage nurse, as well as other data points such aspatient waiting time, patient presence, etc. One or more “vital signacquisition cameras” mounted in the waiting room may be configured toperiodically perform contactless and/or unobtrusive acquisition of onemore updated vital signs and/or physiological parameters from eachpatient. These updated vital signs and/or physiological parameters mayinclude but are not limited to temperature, pulse, oxygen saturation(“SO₂”), respiration rate, skin color, posture, sweat levels, and soforth. In some embodiments, if the updated vital signs and/or adifference between updated and previously-acquired vital signs and/orphysiological parameters (e.g., initial vital signs obtained at triage,previous updated vital signs acquired by the vital sign acquisitioncameras) satisfy one or more thresholds, an alert may be raised tonotify medical personnel of deterioration of the patient. The medicalpersonnel may then take immediate action.

Generally, in one aspect, a method may include: establishing, by one ormore processors, a patient monitoring queue that includes a plurality ofpatients in an area, wherein the area can be captured by one or morevital sign acquisition cameras; unobtrusively acquiring, by one or moreof the vital sign acquisition cameras, one or more updated vital signsfrom a given patient selected from the patient monitoring queue;detecting, by one or more of the processors, based on the one or moreupdated vital signs and prior vital signs acquired previously from thegiven patient, deterioration of the given patient; and providing, by oneor more of the processors, output alerting medical personnel of thedeterioration of the given patient.

In various embodiments, the method may further include receiving, by oneor more of the processors, a patient acuity measure associated with eachpatient of the plurality of patients in the area, wherein the patientacuity measure associated with each patient is based on one or moreinitial vital signs acquired from the patient, and wherein the patientmonitoring queue is ranked based at least in part on the patient acuitymeasures. In various embodiments, the one or more initial vital signsacquired from each patient may be acquired with medical equipment thatis different than the one or more vital sign acquisition cameras.

In various embodiments, the given patient may be selected from thepatient monitoring queue based on a position of the given patient in thepatient monitoring queue. In various embodiments, the method may furtherinclude altering, by one or more of the processors, a position of thegiven patient in the patient monitoring queue based at least in part onan updated patient acuity measure determined in response to the outputalerting medical personnel of the deterioration of the patient.

In various embodiments, the output may include at least one of the givenpatient's name, gender, most recent vital signs, vital sign trend, areference image of the given patient, or a location of the given patientin the area. In various embodiments, the method may further includeidentifying, by one or more of the processors, the given patient amongthe plurality of patients in the area based on a reference imagedepicting the given patient. In various embodiments, the reference imagemay be captured by one or more of the vital sign acquisition cameras. Invarious embodiments, the reference image may be captured by one or morecameras associated with a triage station or registration desk associatedwith the medical waiting room. In various embodiments, the one or morevital sign acquisition cameras includes a pan-tilt-zoom (“PTZ”) camera.

It should be appreciated that all combinations of the foregoing conceptsand additional concepts discussed in greater detail below (provided suchconcepts are not mutually inconsistent) are contemplated as being partof the subject matter disclosed herein. In particular, all combinationsof claimed subject matter appearing at the end of this disclosure arecontemplated as being part of the subject matter disclosed herein. Itshould also be appreciated that terminology explicitly employed hereinthat also may appear in any disclosure incorporated by reference shouldbe accorded a meaning most consistent with the particular conceptsdisclosed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, like reference characters generally refer to the sameparts throughout the different views. Also, the drawings are notnecessarily to scale, emphasis instead generally being placed uponillustrating the principles of the disclosure.

FIG. 1 schematically illustrates a general process flow for patientsmonitored using disclosed techniques, in accordance with variousembodiments.

FIG. 2 illustrates an example environment in which disclosed variouscomponents may implement selected aspects of the present disclosure, inaccordance with various implementations.

FIG. 3 and FIG. 4 each depict an example scenario in which disclosedtechniques may be practiced, in accordance with various embodiments.

FIG. 5 depicts an example method of monitoring individuals in an area,in accordance with various embodiments.

FIG. 6 depicts components of an example computer system.

FIGS. 7 and 8 schematically depict example components of vital signacquisition cameras, in accordance with various embodiments.

DETAILED DESCRIPTION

When patients visit the hospital, they typically are triaged todetermine various information about the patients, such as their names,ages, heights, weights, vital signs, reasons for visiting, and othersimilar information. Once triaged, the patients are sent to an area suchas a waiting room to wait for hospital resources such as physicians tobecome available to examine and/or treat the patients. Wait times forthe patients may be significant depending on availability of hospitalresources. It is not uncommon for patients to deteriorate while waiting,and medical personnel may not always become aware of the deteriorationin a timely fashion. Accordingly, techniques described herein facilitateautomatic and unobtrusive (e.g., contactless) monitoring of patients'conditions in an area such as a waiting room, so that alerts may beprovided to medical personnel when a deterioration of a patient warrantsimmediate medical attention.

The following are definitions of terms as used in the variousembodiments of the present invention. The term “database” as used hereinrefers to a collection of data and information organized in such a wayas to allow the data and information to be stored, searched, retrieved,updated, and manipulated and to allow them to be presented into one ormore formats such as in table form or to be grouped into text, numbers,images, and audio data. The term “database” as used herein may alsorefer to a portion of a larger database, which in this case forms a typeof database within a database. “Database” as used herein also refers toconventional databases that may reside locally or that may be accessedfrom a remote location, e.g., remote network servers. The databasetypically resides in computer memory that includes various types ofvolatile and non-volatile computer storage. Memory wherein the databaseresides may include high-speed random access memory or non-volatilememory such as magnetic disk storage devices, optical storage devices,and flash memory. Memory where the database resides may also compriseone or more software for processing and organizing data received by andstored into the database.

FIG. 1 schematically illustrates generally how patients may be monitoredusing disclosed techniques. In particular, operations and actions aredepicted that may occur in a pre-waiting room area, such as at apre-waiting room area(s) 102, which may include reception and/orregistration, and/or a triage station or booth. In addition, operationsand actions are depicted that may occur in a waiting room 104. At block106, a new patient may enter and/or approach pre-waiting room area(s)102, e.g., after checking in at a reception desk (not depicted).

At block 108, the new patient may be registered. Registration mayinclude, for instance, collecting information about the patient such asthe patient's name, age, gender, insurance information, and reason forvisit. Typically, but not exclusively, this information may be manuallyinput into a computer by medical personnel such as a triage nurse. Insome embodiments, one or more reference images of the patient may beacquired, e.g., by a camera that is integral with a computing deviceoperated by the triage nurse, by a standalone camera, and/or by a vitalsign acquisition camera (in which case at least some vital signs may beoptionally acquired at registration). In many instances, the triagenurse additionally may acquire various initial vital signs and/orphysiological parameters at block 110 using various medical instruments.These initial vital signs and/or physiological parameters may includebut are not limited to blood pressure, pulse, glucose level, SO₂,photoplethysmogram (“PPG”), respiration rate (e.g., breathing rate),temperature, skin color, and so forth. While not depicted in FIG. 1 , insome embodiments, other information may be gathered at triage as well,such as acquiring/updating a patient's medical history, determiningpatient allergies, determining patient's use of medications, and soforth.

Once the patient is registered and their initial vital signs and/orphysiological parameters acquired, at block 112, the patient may be sentto waiting room 104. In some embodiments, the patient may be assigned aso-called “patient acuity measure,” which may be a measure that is usedto rank a severity of the patient's ailment, and in some instances mayindicate an anticipated need for emergency room resources. Any number ofcommonly used indicators and/or clinician decision support (“CDS”)algorithms may be used to determine and/or assign a patient acuitymeasure, including but not limited to the Emergency Severity Index(“ESI”), the Taiwan Triage System (“TTS”), the Canadian Triage andAcuity Scale (“CTAS”), and so forth. For example, in some embodiments,vital signs of the patient may be compared with predefined vital signthresholds stored in a system database, or with published or known vitalsign values typical for a given patient age, gender, weight, etc., todetermine the patient's initial patient acuity measure and/or thepatient's initial position in the patient queue. In some embodiments,various physiological and other information about the patient may be fedinto a trained model (e.g., regression model, neural network, deeplearning network, etc.), case-based reasoning algorithm, or otherclinical reasoning algorithm to derive one or more acuity measures. Insome embodiments, the information used for deriving the acuity measuremay include or even be wholly limited to vitals or other informationthat may be captured by the vital sign acquisition camera. In someembodiments, the information used for deriving the acuity measure mayalternatively or additionally include information such as informationfrom a previous electronic medical record (EMR) of the patient,information acquired from the patient at triage, information fromwearable devices or other sensors carried by the patient, informationabout other patients or people in the waiting room (e.g., vitals ofothers in the room), information about family members or othersassociated with the patient (e.g., family member EMRs), etc.

At block 114, it may be determined, e.g., using one or more cameras,sensors, or input from medical personnel, that a patient has left thewaiting room. Block 114 may include scanning each person currentlywithin the waiting room (e.g., as part of a seeking function thatattempts to locate the patient once the patient is at top of a queue ofpatients for which vitals are to be captured, such as an execution ofblock 120 described below, or cycling through each person in the room tocapture vitals, as multiple executions of the loop including blocks 118and 120 described below) and determining that the patient was notlocated. In some embodiments, the system may wait until a predeterminednumber of instances of the patient missing is reached or a predeterminedamount of time has passed during which the patient is missing before thepatient is deemed to have left the waiting room to account for temporaryabsences (e.g., visiting the restroom or speaking with clinical staff ina triage room). For example, the patient may have been taken into the ERproper because it is their turn to see a doctor. Or the patient'scondition may have improved while they waited, causing them to leave thehospital. Or the patient may have become impatient and left to seek careelsewhere. Whatever the reason, once it is determined that the patienthas left the waiting room for at least a threshold amount of time, atblock 116, the patient may be released from the system, e.g., byremoving them from a queue in which registered patients are entered.

At block 118, a patient in waiting room 104 may be identified formonitoring using techniques described herein. For example, in someembodiments, a database storing registration information obtained atblocks 108-110 may be searched to identify a patient having the highestpatient acuity measure or a patient having the highest acuity measuredthat has not been monitored recently, as may be determined by a timethreshold set for all patients or set (e.g., inversely correlated) basedon the acuity measure). In other embodiments, registration informationassociated with a plurality of patients in waiting room may be ranked ina patient monitoring queue, e.g., by their respective patient acuitymeasures, in addition to or instead of other measures such as waitingtimes, patient presence in the waiting room (e.g., missing patients maybe selected for monitoring more frequently to determine whether theyshould be released if repeatedly absent), etc. In yet other embodiments,patient acuity measures may not be considered when ranking the patientmonitoring queue, and instead only considerations of patient waitingtimes, patient presence, etc., may be considered.

However such a patient monitoring queue is ranked, in some embodiments,the first patient in the queue may be identified as the one to bemonitored next. It is not required (though it is possible) that thepatient monitoring queue be stored in sequence of physical memorylocations ordered by patient acuity measures. Rather, in someembodiments, a ranked patient monitoring queue may merely include a rankor priority level value associated with each patient. In other words, a“patient monitoring queue” as described herein may refer to a “logical”queue that is logically ranked based on patient acuity measures, waitingtime etc., not necessarily a contiguous sequence of memory locations.Patients may be identified for monitoring at block 118 in an order oftheir respective ranking in the patient monitoring queue.

At block 120, the patient identified at block 118 may be located inwaiting room 104. In various embodiments, one or more vital signacquisition cameras (not depicted in FIG. 1 , see FIGS. 2, 7 and 8 )deployed in or near waiting room 104 may be operated to scan variousvisual features of patients in waiting room 104 to match those featuresto a reference patient image captured during registration at block 108.Visual features of patients that may be matched to correspondingfeatures of patient images include but are not limited to faces, hair,clothing, torsos, and so forth.

In other embodiments, no patient monitoring queue may be established.Instead, vital sign acquisition cameras may simple be configured to pan,tilt, and/or zoom so that their respective fields of view move acrosspredetermined trajectories of waiting room 304. For example, vital signacquisition cameras may be configured to sequentially scan across rowsof chairs, and/or to sequentially scan through areas of waiting room 104known to be commonly inhabited by patients. In such embodiments, as eachface is captured, it is matched against patient records to identify thepatient to which the face corresponds so that vitals may be captured andcorrelated to the correct patient or person.

In various embodiments, the system may not be limited to only monitorpatients that have been registered in the system (e.g., according tosteps 108-112). For example, it is possible that a companion of apatient in the waiting room may develop a condition that requiresattention, even though they themselves were not registered as a patient.As another example, a patient may not go through registration 108-112and simply sit down in the waiting room because the waitingroom/registration stations are busy, they do not know to register, theychoose not to register, etc. In such embodiments, the system may detecta non-registered person by capturing an image/video of their face (orcapture other identifying features) and fail to find a matching patientrecord among the registered patients. In such a case, the system maycreate a new record to represent the unknown patient, capture vitals forstorage in the record as initial vitals measurements, and record theimage/video as a reference image (or attempt to capture one or moreadditional images/videos, potentially from better angles, for subsequentuse as reference images). If an alert or other information about theunknown patient is to be displayed to the waiting room staff (e.g., asdescribed below), the information may be displayed along with one ormore of these reference images/videos to aid the staff in identifyingthe person in the waiting room to which the alert or other informationcorresponds. If the person is later registered according to steps108-112, the new information may be merged into the “unknown person”record either manually (e.g., by staff manually selecting the existingrecord which is to be supplemented with registration information) orautomatically (e.g., by later comparing the reference images of the tworecords and determining they correspond to the same person, or by laterencountering difficulty/ambiguity by matching the person to both recordsduring a vitals capture sequence).

At block 122, one or more vital sign acquisition cameras mounted orotherwise deployed in or near waiting room 104 may be operated toperform unobtrusive (e.g., contactless) acquisition of one or moreupdated vital signs and/or physiological parameters from the patientidentified at block 118 and located at block 120. These vital signacquisition cameras may be configured to acquire (without physicallycontacting the patient) a variety of different vital signs and/orphysiological parameters from the patient, including but not limited toblood pressure, pulse (or heart rate), skin color, respiratory rate,PPG, SO₂, temperature, posture, sweat levels, and so forth.

In some embodiments, vital sign acquisition cameras may be equipped toperform so-called “contactless methods” to acquire vital signs and/orextract physiological information from a patient may be used as medicalimage devices. Non-limiting examples of such cameras are described inUnited States Patent Application Publication Nos. 20140192177A1,20140139656A1, 20140148663A1, 20140253709A1, 20140235976A1, and20140275880A1, which are incorporated herein by reference for allpurposes. FIGS. 7 and 8 schematically depict two non-limitingconfigurations of vital sign acquisition cameras that may be employed invarious embodiments of the present disclosure.

In some embodiments, one technique for determining a patient's heartrate or pulse may be to monitor the patient's facial skin color.Micro-changes in skin color that are caused by blood flow may bedetected by a vital sign acquisition camera. These detectedmicro-changes may be used to determine a pulse rate of the patient.Facial skin color changes due to varying heart rate changes may not bevisible to the naked eye, but the use of vital sign acquisition camerasdescribed herein may allow detection of micro-changes in skin color.

Another vital sign measurable by vital sign acquisition camerasdescribed herein is a patient's respiratory rate. In some embodiments, avital sign acquisition camera may zoom in to the patient's chest and/orabdominal area to track the patient's chest or abdominal movements. Themedical image device may then determine the patient's respiratory rateby detecting the patient's rate of inhalation and exhalation, which maybe determined monitoring the movement of the patient's chest ordiaphragm area. In some embodiments, a vital sign acquisition camera maydetermine whether the patient is having difficulty breathing bycomparing the most-recently recorded chest movement patterns withpreviously-recorded chest movement patterns, e.g., stored in a patientsdatabase. Additionally or alternatively, a patient's body temperaturemay be determined by vital sign acquisition cameras described hereinthat are configured to capture thermographic or infrared images/video.

At block 124, it may be determined, e.g., by one or more componentsdepicted in FIG. 2 (described below), based on a comparison of theupdated vital sign(s) and/or physiological parameters acquired at block122 to previously-acquired vital signs and/or physiological parameters(e.g., the initial vital signs acquired at block 110 or a previousiteration of updated vital signs/physiological parameters acquired bythe vital sign acquisition cameras), whether the patient's condition haschanged. For example, it may be determined whether the patient's pulse,respiratory rate, blood pressure, SO2, PPG, temperature, etc. hasincreased or decreased while the patient has waited. If the answer isno, then control may proceed back to block 118, and a new patient (e.g.,the patient with the next highest patient acuity measure) may beidentified and control may proceed back to block 120. However, if theanswer at block 124 is yes (i.e. the patient's condition has changed),then control may pass to block 126. In some embodiments, the patient'scondition may be represented (at least partially) by the same acuitymeasure used for purposes of determining monitoring order.

At block 126, it may be determined (again, by one or more components ofFIG. 2 ) whether a medical alert is warranted based on the changedetected at block 124. For example, it may be determined whether achange in one or more vital signs or patient acuity measures satisfiesone or more thresholds (e.g., has blood pressure increased above a levelthat is considered safe for this particular patient?). If the answer isyes, then control may pass to block 128. At block 128, an alarm may beoutput, e.g., to a duty nurse or other medical personnel, that thepatient is deteriorating. The medical personnel may then check on thepatient to determine if remedial action, such as immediately admittingthe patient or sending the patient to a doctor, is warranted. In someembodiments, control may then pass back to block 118. However, if theanswer at block 126 is no, then in some embodiments, control may passback to block 118.

FIG. 2 depicts example components that may be used to practice disclosedtechniques, in accordance with various embodiments. A hospitalinformation system 240 may be of the type that is commonly found inhospitals, doctor's offices, and so forth. Hospital information system240 may be implemented using one or more computing systems that may ormay not be connected via one or more computer networks (not depicted).Hospital information system 240 may include, among other things, aregistration module 242, a triage module 244, a release module 246, andan alarm module 248. One or more of modules 242-248, or any other moduleor engine described herein, may be implemented using any combination ofhardware and software, including one or more microprocessors executinginstructions stored in memory. For example, the registration module 242may include registration instructions implementing the functionalitydescribed herein in connection with registration executing on aprocessor while the triage module 244 may include triage instructionsimplementing the functionality described herein in connection withtriage executing on the same processor. Similar underlying hardware andsoftware may be used to implement other “modules” described herein.

Registration module 242 may be configured to receive, e.g., as manualinput from a duty nurse, registration information of new patients. Thismay include, for instance, the patient's name, age, insuranceinformation, and so forth. Triage module 244 may be configured toreceive, e.g., as manual input from a duty nurse or directly fromnetworked medical equipment, vital signs such as those described aboveand/or other physiological data, such as weight, height, the patient'sreason for the visit, etc. In various embodiments, vital signs receivedby triage module 244 and/or a patient acuity measure (e.g., ESI in FIG.1 ) may be associated with corresponding patient information received byregistration module 242, e.g., in one or more databases (not depicted)associated with hospital information system 240.

Alarm module 248 may be configured to receive information indicative ofvarious events, such as patient deterioration, and raise various alarmsand/or alerts in response. These alarms and/or alerts may be outputusing a variety of modalities, including but not limited to visualoutput (e.g., on display screens visible to hospital personnel),intercom announcements, text messages, emails, audio alerts, hapticalerts, pages, pop up windows, flashing lights, and so forth. Modules242-248 of hospital information system 240 may be operably coupled,e.g., via one or computer networks (not depicted), to a hospitalinformation system interface 250 (“H.I.S. Interface” in FIG. 2 ).

Hospital information system interface 250 may serve as an interfacebetween the traditional hospital information system 240 and a patientmonitoring system 252 configured with selected aspects of the presentdisclosure. In various embodiments, the hospital information systeminterface 250 may publish, e.g., to other modules of the patientmonitoring system 252, various information about patients such asregistration information, patient acuity measures (e.g., ESI),prescribed and/or administered medications, whether a patient has beenreleased, various alarms/alerts, and so forth. As will be describedbelow, in some embodiments, these publications may be provided to anevent publish and subscribe (“EPS”) module 270, which may thenselectively store them in database 272 and/or selectively publish themto other modules of patient monitoring system 252. In some embodiments,hospital information system interface 250 may additionally oralternatively subscribe to one or more alerts or publications providedby other modules. For example, hospital information system interface 250may subscribe alerts from deterioration detection module 268, e.g., sothat hospital information system interface 250 may notify appropriatecomponents of hospital information system 240, such as alarm module 248,that a patient is deteriorating.

Patient monitoring system 252 may include a variety of components thatfacilitate monitoring of patients in an area such as waiting room 104 toensure that patients are served in a manner conducive with their actualmedical condition. Patent monitoring system 252 may include, forinstance, a patient capture module 254 that interfaces with one or morecameras 256, a patient queue module 258, a patient identification module260, a dynamic calibration module 262, a face/torso acquisition module264, a vital signs measurement module 266, a deterioration detectionmodule 268, the aforementioned EPS module 270, and one or more databases272, 274. As noted above, each of modules 250, 254, and 258-274 may beimplemented using any combination of hardware and software. And whilethese modules are depicted separately, that is not meant to be limitingor to suggest each is implemented on a separate piece of hardware. Forexample, one or more modules may be combined and/or omitted, and one ormore modules may be implemented on one or more computing systemsoperably connected via one or more computer networks (not depicted). Thelines depicted connecting various components of FIG. 2 may representcommunication channels accessible to these components. Thesecommunication channels may be implemented using any number of networkingor other computer communication technologies, such as one or more buses,Ethernet, Wi-Fi, Bluetooth, Z-Wave, ZigBee, cellular communication, andso forth.

Patient monitoring system 252 may also include one or more vital signacquisition cameras 276 that are configured to acquire, e.g., from somedistance from a patient, one or more vital signs and/or physiologicalparameters of the patient. Examples of such vital sign acquisitioncameras were described above. In various embodiments, a vital signacquisition camera 276 may be a pan-tilt-zoom (“PTZ”) camera that isoperable to pan, tilt, and zoom so that different parts of an area suchas waiting room 104 are contained within its field of view. In thismanner, it is possible to scan the area being monitored to locatedifferent patients, so that updated vital signs and/or physiologicalparameters may be acquired unobtrusively.

Patient capture module 254 may receive, from one or more cameras 256,one or more signals carrying captured image data of a patient. Forexample, in some embodiments, patient capture module 254 may receive avideo stream from camera 256. Patient capture module 254 may performimage processing (e.g., face detection, segmentation, shape detection todetect human form, etc.) on the video stream to detect when a patient ispresent, and may capture a reference image of the patient in response tothe detection. In some embodiments, the reference image may be capturedat a higher resolution than individual frames of the video stream,although this is not required. In some embodiments, camera 256 may be astandalone camera, such as a webcam, a PTZ camera (e.g., 276), and soforth, that is deployed in or near pre-waiting room area(s) 102. The oneor more images captured by camera 256 may be used thereafter asreference patient images that is associated with the patient and usedlater to identify the patient in the area being monitored.

Patient queue module 258 may be configured to establish and/or maintaina priority queue, e.g., in a database, of patients in the area beingmonitored. In various embodiments, the queue may be ordered by variousparameters. In some embodiments, patients in the queue may be ranked inorder of patient acuity measures (i.e. by priority). For example, themost critical patients may be placed near the front of the queue andless critical patients may be placed near the end of the queue, or viceversa. In some embodiments, updated vital signs may be acquired frompatients waiting in the area being monitored, such as waiting room 104,in an order of the queue. In other embodiments, updated vital signs maybe acquired from patients in a FIFO or round robin order. In otherembodiments, updated vital signs may be acquired from patients in anorder that corresponds to a predetermined scan trajectory programmedinto vital sign acquisition camera 276 (e.g., scan each row of chairs inorder).

Patient identification module 260 may be configured to use one or moresignals received from vital sign acquisition camera 276, in conjunctionwith one or more reference patient images captured by patient capturemodule 254, to locate one or more patients in the area being monitored(e.g., waiting room 104). Patient identification module 260 may usevarious image processing techniques to identify patients using variousvisual features of patients. These visual features that may be used torecognize patients may include but are not limited to facial features,torso features, clothing, hair, posture, and so forth.

In some embodiments, patient identification module 260 may search anarea being monitored for particular patients from which to obtainupdated vital signs. For example, patient identification module 260 maysearch the area being monitored for a patient identified by patientqueue module 258, which may be, for instance, the patient in the queuehaving the highest patient acuity measure. In some embodiments, patientidentification module 260 may cause vital sign acquisition camera(s) 276to scan the area being monitored (e.g., waiting room 104) until theidentified patient is identified.

Dynamic calibration module 262 may be configured to track the use ofvital sign acquisition camera(s) 276 and calibrate them as needed. Forinstance, dynamic calibration module 262 may ensure that whenever vitalsign acquisition camera 276 is instructed to point to a particular PTZlocation, it always points to the same place. PTZ cameras may be inconstant or at least frequent motion. Accordingly, their mechanicalcomponents may be subject to wear and tear. Small mechanicalerrors/biases may accumulate and cause vital sign acquisition camera 276to respond, over time, differently to a given PTZ command. Dynamiccalibration module 262 may correct this, for instance, by occasionallyrunning a calibration routine in which landmarks (e.g., indicia such assmall stickers on the wall) may be used to train a correction mechanismthat will make vital sign acquisition camera 276 respond appropriately

Once a patient identified from patient queue 258 is recognized bypatient identification module 260, face/torso acquisition module 264 maybe configured to pan, tilt, and/or zoom one or more vital signacquisition cameras 276 so that their fields of view capture a desiredportion of the patient. For example, in some embodiments, face/torsoacquisition module 264 may pan, tilt, or zoom a vital sign acquisitioncamera 276 so that it is focused on a patient's face and/or torso.Additionally or alternatively, face/torso acquisition module 264 maypan, tilt, or zoom one vital sign acquisition camera 276 to capture thepatient's face, and another to capture the patient's torso. Variousvital signs and/or physiological parameters may then be acquired. Forinstance, vital signs such as the patient's pulse, SpO₂, respiratoryrate, and blood pressure may be obtained, e.g., by vital signsmeasurement module 266, by performing image processing on an image/videoof the patient's face captured by vital sign acquisition camera(s) 276.Vital signs and/or physiological parameters such as the patient'srespiratory rate, general posture (which may indicate pain and/orinjury), and so forth may be obtained, e.g., by vital signs measurementmodule 266, by performing image processing on an image/video of thepatient's torso captured by vital sign acquisition camera(s) 276. Ofcourse, the face and torso are just two examples of body portions thatmay be examined to obtain vital signs, and are not meant to be limiting.

Deterioration detection module 268 may be configured to analyze one ormore signals to determine whether a condition of a registered patient isdeteriorating, improving, and/or remaining stable. In some embodiments,the patient condition may be represented, at least in part, by the samepatient acuity measures described above for determining order ofpatients for monitoring. As such, the deterioration detection module 268may include one or more CDS, case-based reasoning, or other clinicalreasoning algorithms as described herein or other clinical reasoningalgorithms (e.g., trained logistic regression models or other machinelearning models) for assessing patient condition measures other thanacuity measures described herein. In some embodiments, the algorithmsfor assessing patient acuity or other measures of patient conditionemployed by the deterioration detection module 268 may be updated fromtime to time by, for example, writing new trained weights (e.g., thetavalues) for a selected machine learning module or providing newinstructions for execution by a processor (e.g. in the form of a javaarchive, JAR, file or compiled library). These signals may include, forinstance, a patient's initial vital signs and other physiologicalinformation (e.g., obtained at blocks 108-110 of FIG. 1 ), updated vitalsigns obtained by vital signs measurement module 266, a patients initialpatient acuity measure (e.g., calculated during registration), and/or apatient's updated patient acuity measure (e.g., calculated based onupdated vital signs and/or physiological parameters received from vitalsigns measurement module 266). Based on determinations made using thesesignals, deterioration detection module 268 may send various alerts tovarious other modules to take various actions. For example,deterioration detection module 268 may publish an alert, e.g., bysending the alert to EPS module 270 so that EPS module can publish thealert to subscribed modules, such as alarm module 240 of hospitalinformation system 240. In some embodiments, such an alert may include,for instance, a patient's name (or more generally, a patientidentifier), a picture, the patient's last detected location in thewaiting room, baseline vital signs, one or more updated vital signs,and/or an indication of a patient acuity measure. On receipt of thealert, alarm module 248 may raise an alert or alarm to medical personnelof the patient's deterioration and, among other things, the patient'slast detected location in the waiting room.

EPS module 270 may be a general communication hub that is configured todistribute events released by various other components of FIG. 2 . Insome embodiments, all or at least some of the other modules depicted inFIG. 2 may generate events that indicate some form ofresult/determination/computation/decision from that module. These eventsmay be sent, or “published,” to EPS module 270. All or some of the othermodules depicted in FIG. 2 may elect to receive, or “subscribe to,” anyevent from any other module. When EPS module 270 receives an event, itmay sent data indicative of the event (e.g., forward the event) to allmodules that have subscribed to that event.

In some embodiments, EPS module 270 may be in communication with one ormore databases, such as database 272 and/or archive 274 (which may beoptional). In some embodiments, EPS module 270 may accept remoteprocedure calls (“RPC”) from any module to provide access to informationstored in one or more databases 272 and/or 274, and/or to addinformation (e.g., alerts) received from other modules to databases 272and/or 274. Database 272 may store information contained in alerts,publications, or other communications sent/broadcast/transmitted by oneor more other modules in FIG. 2 . In some embodiments, database 272 maystore, for instance, reference images associated with patients and/ortheir initial vital signs, updated vital signs (acquired by vital signacquisition camera 276), and/or patient acuity measures. Optionalarchive 274 may in some embodiments store the same or similarinformation for a longer period of time.

It will be apparent that various hardware arrangements may be utilizedto implement the patient monitoring system 252. For example, in someembodiments, a single device may implement the entire system 252 (e.g.,a single server to operate the camera 276 to perform the vitalsacquisition functions 260-266 and to perform the vitals analysis andalerting functions including deterioration detection 268 and queuemanagement 258). In other embodiments, multiple independent devices mayform the system 252. For example, a first device may drive the camera276 and implement functions 260-266 while another server may perform theremaining functions. In some such embodiments, one device may be localto the waiting room while another may be remote (e.g., implemented as avirtual machine in a geographically distant cloud computingarchitecture). In some embodiments, a device (e.g., including aprocessor and memory) may be disposed within the camera 276 itself and,as such, the camera 276 may not simply be a dumb peripheral and, insteadmay perform the vital signs functions 260-266. In some such embodiments,another server may provide indications (e.g. identifiers, full records,or registered facial images) to the camera 276 to request that vitals bereturned for further processing. In some such embodiments, additionalfunctionality may be provided on-board the camera 276 such as, forexample, the deterioration detection 268 (or preprocessing therefor)and/or patient queue 258 management may be performed on-board the camera276. In some embodiments, the camera 276 may even implement the HISinterface 250 or EPS 270. Various additional arrangements will beapparent.

FIG. 3 illustrates an example scenario in which disclosed techniques maybe implemented to monitor a plurality of patients 378A-C in a waitingroom 304. In this example, three patients 378A-C are waiting in ahospital waiting room 304 to be attended to by medical personnel 380.Two video cameras 376A, 376B are mounted on a surface (e.g., ceiling,wall) of waiting room 304. The two video cameras 376A, 376B may be usedto monitor patients 378 in waiting room 304. The patients 378A-C mayeach be assigned a patient acuity measure by triaging medical personnel(not depicted) based on a preliminary patient condition analysis. As thepatients 378 wait for an attending physician, the two video cameras376A, 376B may monitor patients 378 as described above to detect patientdeterioration. In some embodiments, a patient acuity measure associatedwith a patient may be updated by medical personnel in response todetection by patient monitoring system (more specifically, deteriorationdetection module 268) that a patient has deteriorated. In variousembodiments, when a new patient enters waiting room 304, a new round ofpatient monitoring and prioritization may be performed, e.g., by patientmonitoring system 252. The patient queue may be automatically updated,e.g., by patient queue module 258, each time a new patient enterswaiting room 304. Additionally or alternatively, medical personnel maymanually update the patient queue to include a newly-arrived patientafter triaging.

In some embodiments, one or more updated vital signs and/orphysiological parameters of the patients 378 may be acquired using videocameras 376A, 376B to detect, for example, abnormal face color or colorchange such as flushing or greyish pallor. Additionally oralternatively, vital sign acquisition cameras 376 may analyze patients378 for abnormal breathing patterns such as heavy or irregularbreathing. An image or video of a patient with a very pale skin colorthat also depicts the patient experiencing shortness of breath may becompared to the patient's reference image, e.g., stored by hospitalinformation system 240, to determine that the patient is experiencing aheart attack. In such a scenario, an alert may be sent immediately tomedical personnel, e.g., by text message, intercom announcement, outputon a display screen, etc.

Suppose that in FIG. 3 , first patient 378A is a student waiting for theresults of his blood and urine test, second patient 378B is waiting toreceive treatment for a sports injury, while third patient 378C needs tosee a doctor regarding some stomach pains. Suppose a fourth patient378D, who was earlier waiting to see a physician for some minorbreathing difficulty, was detected by video cameras 376A, 376B toexhibit some symptoms warranting emergency care. An alert such as anaudio or visual alert may be raised to notify medical personnel of thedeterioration of fourth patient 378D. Upon receiving the alert,emergency personnel 380 may take fourth patient 378D to the emergencyroom 384 where she receives the necessary treatment. Once fourth patient378D is taken to emergency room 384, the patient queue may be updated toinclude only those patients 378A-C still waiting for their turn inwaiting room 304.

Techniques described herein are not limited to hospital waiting rooms.There are numerous other scenarios in which techniques described hereinmay be implemented to achieve a variety of technical advantages. Forexample, disclosed techniques may also be used for security monitoringof crowds in airports, arenas, and other public places. In suchscenarios, rather than monitoring patients to determine patient acuitymeasures, individuals may be monitored for other types of measurements,such as risk measurements.

As another example, FIG. 4 depicts how disclosed techniques may beimplemented in a gym. Two vital sign acquisition cameras 476A, 476B arestrategically located to cover every angle required for monitoring eachathlete in the gym, e.g., so that they can be used to monitor athletes478A-B. A training instructor 486 (e.g., a coach, fitness instructor, orphysical therapist) may first assess the physical condition of athletes478 by, for example, determining whether a particular athlete feels painduring stretching due to the athlete's previous physical injury. Whenfirst athlete 478A passes the assessment, training instructor 486 maydirect first athlete 478A to begin a standard training regimen. In thisexample, as first athlete 478A performs the assigned trainingregimen—for example, using the treadmill—his vital signs and/orphysiological parameters such as heart rate, respiratory rate, andtemperature may be continuously/periodically monitored by vital signacquisition cameras 476A, 476B, e.g., to determine whether first athlete478A is over-exerting himself.

In some embodiments, at the start of the monitoring process, e.g., whenfirst athlete 478A enters the gym to workout, one of the two vital signacquisition cameras 476 may identify first athlete 478A, e.g., based ona reference image captured previously (e.g., when first athlete 478joined the gym and received a photo ID). Vital sign acquisition camera476A may zoom in to a facial area of first athlete 478A to acquire aheart rate, and then may zoom in a chest area of first athlete 478A toacquire a respiratory rate. The acquired vital signs may be transmittedby vital sign acquisition camera 476A to a computing device (notdepicted, one or more components of patient monitoring system 252) forfurther analysis, and may be stored in a database (e.g., 272, 274). Ifthe acquired vital signs exceed a certain threshold level, anotification (e.g., in the form of audible signal or a visual alert) maybe generated to alert training instructor 486 about the exceededthreshold. In some embodiments, the computing device may recommendspecific steps to be performed by first athlete 476A, such as stretchingand adequate breaks between training sessions. Similar techniques may beapplied to other athletes, such as second athlete 478B, depending ontheir respective health conditions. In some embodiments, rather thanmonitoring for signs of injury, techniques described herein may be usedin a gym or similar setting to track calories burned or otherphysiological metrics, e.g., based on athlete movement, weight,temperature, pulse, respiration rate, etc., that are tracked by vitalsign acquisition cameras 476 over time. To adapt the system of FIG. 2 tothis setting, the deterioration detection module 268 may simply beprovided with an algorithm for deriving calorie burn (or other metrics)from the available parameters. In some embodiments, the system mayinclude a competitive component such as, for example, a display visibleto people in the room showing the calories burned or other metrics ofeach person in the room, potentially ranked in order of highest caloriesburned or best other metrics observed.

FIG. 5 depicts an example method 500 for monitoring a plurality ofindividuals such as patients in an area such as a waiting room, gym, andso forth. For convenience, some of the operations of method 500 aredescribed with reference to a system that performs the operations. Thissystem may include various components of various computer systems. Forinstance, some operations may be performed by one or more components ofpatient monitoring system 252. Moreover, while operations of method 500are shown in a particular order, this is not meant to be limiting. Oneor more operations may be reordered, omitted or added.

At block 502, individual health indices (e.g., patient acuity measure,workout intensity measure, ESI, etc.) may be received, e.g., frommedical personnel (e.g., at triage), for a plurality of individuals(e.g., patients, athletes, residents of a nursing home, etc.) located inan area such as a waiting room that is capable of being captured infields of view of the above-described vital sign acquisition cameras(which as noted above may have adjustable fields of view by virtue ofpanning, tilting, and/or zooming). For example, in various embodiments,prior to entering the monitored area, one or more initial vital signsand/or physiological parameters may be acquired from each individual,e.g., by a triage nurse or trainer. Based on these initial vital signsand/or physiological parameters, individual health indices may bedetermined, e.g., by medical personnel, for each individual in the areaat block 502.

At block 504, the system may establish (or update, if it already exists)a queue (e.g., a patient queue) of individuals in the area. In variousembodiments, the queue may be ordered and/or ranked based at least inpart on the individual health indices determined at block 502.Additionally or alternatively, in some embodiments, the queue may beordered based on other data points, including but not limited to thetime each patient arrived, how long each patient has waited, and soforth. In some embodiments, when flow returns from block 512 or 514,block 504 may include placing the most recently monitored patient backon the queue (or otherwise placing a new entry for the patient in thequeue). For example, in some embodiments, the patient may simply beplaced at the end of the queue. In other embodiments, block 504 may takethe patient acuity measure, deterioration measure, vitals, or otherinformation into account such as, for example, placing the patient at aposition in the queue after any patients having higher acuity measuresbut ahead of any patients having lower acuity measures. In otherembodiments, more complex rules may be employed. For example, in someembodiments, the patient may be placed back in the queue as describedbut no higher than fifth (or other constant value) from the top to thequeue, to help prevent the same (highest acuity) patient from beingmonitored repeatedly but not allowing monitoring of other patients(because they never reach the top of the queue). Alternatively, ratherthan a constant maximum position, the maximum position may be determinedbased on the current contents of the queue. For example, the maximumposition may be set to equal the number (or a constant plus the number)of “high acuity” patients, identified as those patients having a patientacuity measure surpassing a preset threshold. In some embodiments, suchhigh acuity patients may be placed at an intermediate point in the queue(according to any of the methods described herein), while others may beplaced at the end of the queue. In other embodiments, the patient may beplaced at a position from the front equal to the number of patientshaving a higher acuity measure in the queue plus one (or some otherconstant) to allow at least some lower acuity patients to be monitoredahead of the current patient. In some embodiments, acuity measure values(or ranges thereof) may be associated with a delay between subsequentmeasurements measured in, for example, number of queue positions or realtime between measurements, which may then be translated into theposition of the queue where the patient will be placed. In someembodiments, the patient acuity measure (or other value driving queueposition placement) may take into account the time that has passed sincethe patient was last monitored; as such, as a patient sits in the queue,their acuity measure (or other queue position determining value) maygradually increase, making it more difficult for other patients to beplaced ahead of that patient in the queue. In some such embodiments, a“queue priority value” may be utilized in the manner described above asapplied to the patient acuity measure but may equal the patient acuitymeasure plus the time since the patient was last monitored (or someweighted sum of these two or additional values).

At block 506, the system may select a given individual from whichupdated vital signs and/or physiological parameters are to be acquired.For example, the system may select a patient from the front of the queueestablished in block 504 or may select a patient having a highestpatient acuity measure (which in many embodiments may be the firstpatient in the queue). In other embodiments, the system may selectindividuals in different orders, such as using FIFO and/or round robin.

At block 508, the individual selected at block 506 may be identified inthe monitored area by one or more vital sign acquisition camera 276,e.g., based on one or more reference images of the individual. As notedabove, various visual features of individuals may be used foridentification, including but not limited to facial features, posture,clothing, size, and so forth. At block 510, one or more vital signacquisition camera 276 may unobtrusively acquire one or more updatedvital signs and/or physiological parameters from the individual selectedat block 506 and identified at block 508. In various embodiments,individuals may opt out of unobtrusive acquisition, e.g., by notifying atriage nurse or other personnel.

In some embodiments, at block 512, deterioration in the individualselected at block 506 and identified at block 508 may be detected basedon the updated vital signs obtained at block 510 and at least one of anindividual health index (e.g., patient acuity measure) associated withthe given patient (e.g., determined at block 502) or initial vital signs(or updated vital signs acquired during a previous iteration of patientmonitoring system 252) acquired from the given patient. If deteriorationis detected, e.g., due to a difference between initial and updated vitalsigns satisfying a threshold, the method 500 may proceed to block 514.At block 514, various modalities of output, including but not limited totext messages, intercom announcements, visual output, audio output,haptic feedback, etc., may be provided to alert pertinent personnel ofthe difference, e.g., to notify a duty nurse of deterioration of apatient. In some embodiments, for example, medical personnel may bealerted of patient deterioration by displaying either a most-recentlycaptured image of the deteriorating patient (e.g., so that medicalpersonnel will know who to look for in the waiting room) or a livestreaming video of the deteriorating patient in the waiting room.Regardless of whether method 500 proceeds to block 514 after block 512,method 500 may proceed back to block 504 to update the queue, e.g., toreorder the queue so that the patient having the next highest patientacuity measure may be monitored).

While examples described herein have primarily involved vital signacquisition cameras such as cameras configured to perform contactlessacquisition of vital signs and/or physiological parameters, this is notmeant to be limiting. In various embodiments, other types of sensors maybe incorporated into vital sign acquisition cameras and/or deployedseparately to detect vital signs and/or physiological parameters ofpatients. For example, motion sensors may be used, for example, todetect abnormal motions of a patient in a waiting room such as those dueto a patient undergoing a seizure. Various types of motion sensors maybe employed, including but not limited to infrared, optical, microwave,ultrasonic, acoustic, or tomographic based sensors, as well as thosethat fall under the category of occupancy sensors. Motion sensors may bepassive and/or dynamic. Passive infrared sensors, for instance, detectheat movement by way of a pyroelectric sensor designed to detectinfrared radiation radiated by a moving body. Ultrasonic sensors, bycontrast, may leverage the Doppler-shift principle. An ultrasonic sensormay transmit high frequency sound waves in a monitored area and detectreflected wave patterns. Microwave sensors may work in a similar fashionexcept that they may transmit high frequency microwaves rather thansound waves.

FIG. 6 is a block diagram of an example computer system 610. Computersystem 610 typically includes at least one processor 614 whichcommunicates with a number of peripheral devices via bus subsystem 612.As used herein, the term “processor” will be understood to encompassvarious devices capable of performing the various functionalitiesattributed to the CDS system described herein such as, for example,microprocessors, FPGAs, ASICs, other similar devices, and combinationsthereof. These peripheral devices may include a data retention subsystem624, including, for example, a memory subsystem 625 and a file storagesubsystem 626, user interface output devices 620, user interface inputdevices 622, and a network interface subsystem 616. The input and outputdevices allow user interaction with computer system 610. Networkinterface subsystem 616 provides an interface to outside networks and iscoupled to corresponding interface devices in other computer systems.

User interface input devices 622 may include a keyboard, pointingdevices such as a mouse, trackball, touchpad, or graphics tablet, ascanner, a touchscreen incorporated into the display, audio inputdevices such as voice recognition systems, microphones, and/or othertypes of input devices. In general, use of the term “input device” isintended to include all possible types of devices and ways to inputinformation into computer system 610 or onto a communication network.

User interface output devices 620 may include a display subsystem, aprinter, a fax machine, or non-visual displays such as audio outputdevices. The display subsystem may include a cathode ray tube (CRT), aflat-panel device such as a liquid crystal display (LCD), a projectiondevice, or some other mechanism for creating a visible image. Thedisplay subsystem may also provide non-visual display such as via audiooutput devices. In general, use of the term “output device” is intendedto include all possible types of devices and ways to output informationfrom computer system 610 to the user or to another machine or computersystem.

Data retention system 624 stores programming and data constructs thatprovide the functionality of some or all of the modules describedherein. For example, the data retention system 624 may include the logicto perform selected aspects of method 500, and/or to implement one ormore components of patient monitoring system 252.

These software modules are generally executed by processor 614 alone orin combination with other processors. Memory 625 used in the storagesubsystem can include a number of memories including a main randomaccess memory (RAM) 630 for storage of instructions and data duringprogram execution, a read only memory (ROM) 632 in which fixedinstructions are stored, and other types of memories such asinstruction/data caches (which may additionally or alternatively beintegral with at least one processor 614). A file storage subsystem 626can provide persistent storage for program and data files, and mayinclude a hard disk drive, a floppy disk drive along with associatedremovable media, a CD-ROM drive, an optical drive, or removable mediacartridges. The modules implementing the functionality of certainimplementations may be stored by file storage subsystem 626 in the dataretention system 624, or in other machines accessible by theprocessor(s) 614. As used herein, the term “non-transitorycomputer-readable medium” will be understood to encompass both volatilememory (e.g. DRAM and SRAM) and non-volatile memory (e.g. flash memory,magnetic storage, and optical storage) but to exclude transitorysignals.

Bus subsystem 612 provides a mechanism for letting the variouscomponents and subsystems of computer system 610 communicate with eachother as intended. Although bus subsystem 612 is shown schematically asa single bus, alternative implementations of the bus subsystem may usemultiple busses.

Computer system 610 can be of varying types including a workstation,server, computing cluster, blade server, server farm, or any other dataprocessing system or computing device. In some embodiments, computersystem 610 may be implemented within a cloud computing environment. Dueto the ever-changing nature of computers and networks, the descriptionof computer system 610 depicted in FIG. 6 is intended only as a specificexample for purposes of illustrating some implementations. Many otherconfigurations of computer system 610 are possible having more or fewercomponents than the computer system depicted in FIG. 6 .

FIG. 7 shows a schematic diagram of a first embodiment of a vital signacquisition camera 776 that may be employed in various embodimentsdescribed herein. Electromagnetic radiation 782, in particular light inthe visible and infrared wavelength range, reflected from a living being784, such as a patient, is received and evaluated by said camera 776 togenerate a biometrical signal 798 of the living being 784. The camera776 may include a filter 786 for blocking incident visible light withinthe incident electromagnetic radiation 782 in a wavelength range up tosubstantially 550 nm, and/or up to approximately 600 nm, and/or up to650 nm. The filtered incident light 788 is then sensed by a color sensor790 that generates at least two different color signals 792 _(A), 792_(B), e.g. by use of two separate color detectors 793, 794 (or an arrayof such color detectors). A combination unit 795 generates at least onecombined color signal 796 by combining said color signals 792 _(A), 792_(B), e.g. by a linear combination. Finally, a processing unit 797 isprovided for processing said combined color signal 796 and extracting atleast one biometrical signal 798 of the living being 784. Thecombination unit 795 and the processing unit 797 may be realized in someembodiments by a common processor 799, e.g. as processing elements of aprocessor or implemented in software on a conventional processor.However, they may also be realized in a different manner, e.g. asdedicated hardware elements.

FIG. 8 schematically shows a second embodiment of a camera 876′ that maybe employed in various embodiments described herein. FIG. 8 shows thatoptionally an additional filter 886′ may be provided (in this and/orother embodiments), which filter 886′ is configured to block incidentlight in a wavelength range above at least 1100 nm, in particular aboveat least 1000 nm, before reaching the color sensor 890. While generallythose color sensors, e.g. imaging silicon sensors, show a sensitivitythat naturally decreases towards longer wavelengths, such an additionalfilter 886′ may ensure that signal contributions within the filteredincident light 888 above said upper threshold wavelength are blocked,i.e. signal contributions in which water absorption becomes dominant areblocked in the twice filtered incident light 888′.

Further, in this embodiment the color sensor 890 generates threedifferent color signals 892 _(A), 892 _(B), 892 _(C), e.g. by use of acolor filter array 893 having three different color filter areasprovided in front of a photo detector 895 (or, more generally, the imagesensor). Such a color sensor (e.g. including a color filter array havingonly two color filter areas) could also be used in the embodiment shownin FIG. 7 . In some embodiments, the color sensor 890 may include acolor filter array generating a red color signal 892 _(A), a green colorsignal 892 _(B) and a blue color signal 892 _(C) as conventionallyprovided by an RGB color sensor. From the three color signals 892 _(A),892 _(B), 892 _(C), the combination unit 895 generates two combinedcolor signals 896 _(A), 896 _(B) by making two different combinations,in particular linear combinations, of at least two of said three colorsignals 892 _(A), 892 _(B), 892 _(C). From these two combined colorsignals 896 _(A), 896 _(B) the processing unit then finally extracts thedesired biometrical signal 898 from the living being 884.

While several embodiments have been described and illustrated herein,those of ordinary skill in the art will readily envision a variety ofother means and/or structures for performing the function and/orobtaining the results and/or one or more of the advantages describedherein, and each of such variations and/or modifications is deemed to bewithin the scope of the embodiments described herein. More generally,those skilled in the art will readily appreciate that all parameters,dimensions, materials, and configurations described herein are meant tobe exemplary and that the actual parameters, dimensions, materials,and/or configurations will depend upon the specific application orapplications for which the teachings is/are used. Those skilled in theart will recognize, or be able to ascertain using no more than routineexperimentation, many equivalents to the specific embodiments describedherein. It is, therefore, to be understood that the foregoingembodiments are presented by way of example only and that, within thescope of the appended claims and equivalents thereto, embodiments may bepracticed otherwise than as specifically described and claimed.Inventive embodiments of the present disclosure are directed to eachindividual feature, system, article, material, kit, and/or methoddescribed herein. In addition, any combination of two or more suchfeatures, systems, articles, materials, kits, and/or methods, if suchfeatures, systems, articles, materials, kits, and/or methods are notmutually inconsistent, is included within the scope of the presentdisclosure.

All definitions, as defined and used herein, should be understood tocontrol over dictionary definitions, definitions in documentsincorporated by reference, and/or ordinary meanings of the definedterms.

The indefinite articles “a” and “an,” as used herein in thespecification and in the claims, unless clearly indicated to thecontrary, should be understood to mean “at least one.”

The phrase “and/or,” as used herein in the specification and in theclaims, should be understood to mean “either or both” of the elements soconjoined, i.e., elements that are conjunctively present in some casesand disjunctively present in other cases. Multiple elements listed with“and/or” should be construed in the same fashion, i.e., “one or more” ofthe elements so conjoined. Other elements may optionally be presentother than the elements specifically identified by the “and/or” clause,whether related or unrelated to those elements specifically identified.Thus, as a non-limiting example, a reference to “A and/or B”, when usedin conjunction with open-ended language such as “comprising” can refer,in one embodiment, to A only (optionally including elements other thanB); in another embodiment, to B only (optionally including elementsother than A); in yet another embodiment, to both A and B (optionallyincluding other elements); etc.

As used herein in the specification and in the claims, “or” should beunderstood to have the same meaning as “and/or” as defined above. Forexample, when separating items in a list, “or” or “and/or” shall beinterpreted as being inclusive, i.e., the inclusion of at least one, butalso including more than one, of a number or list of elements, and,optionally, additional unlisted items. Only terms clearly indicated tothe contrary, such as “only one of” or “exactly one of,” or, when usedin the claims, “consisting of,” will refer to the inclusion of exactlyone element of a number or list of elements. In general, the term “or”as used herein shall only be interpreted as indicating exclusivealternatives (i.e. “one or the other but not both”) when preceded byterms of exclusivity, such as “either,” “one of,” “only one of,” or“exactly one of.” “Consisting essentially of,” when used in the claims,shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase “atleast one,” in reference to a list of one or more elements, should beunderstood to mean at least one element selected from any one or more ofthe elements in the list of elements, but not necessarily including atleast one of each and every element specifically listed within the listof elements and not excluding any combinations of elements in the listof elements. This definition also allows that elements may optionally bepresent other than the elements specifically identified within the listof elements to which the phrase “at least one” refers, whether relatedor unrelated to those elements specifically identified. Thus, as anon-limiting example, “at least one of A and B” (or, equivalently, “atleast one of A or B,” or, equivalently “at least one of A and/or B”) canrefer, in one embodiment, to at least one, optionally including morethan one, A, with no B present (and optionally including elements otherthan B); in another embodiment, to at least one, optionally includingmore than one, B, with no A present (and optionally including elementsother than A); in yet another embodiment, to at least one, optionallyincluding more than one, A, and at least one, optionally including morethan one, B (and optionally including other elements); etc.

It should also be understood that, unless clearly indicated to thecontrary, in any methods claimed herein that include more than one stepor act, the order of the steps or acts of the method is not necessarilylimited to the order in which the steps or acts of the method arerecited.

In the claims, as well as in the specification above, all transitionalphrases such as “comprising,” “including,” “carrying,” “having,”“containing,” “involving,” “holding,” “composed of,” and the like are tobe understood to be open-ended, i.e., to mean including but not limitedto. Only the transitional phrases “consisting of” and “consistingessentially of” shall be closed or semi-closed transitional phrases,respectively, as set forth in the United States Patent Office Manual ofPatent Examining Procedures, Section 2111.03. It should be understoodthat certain expressions and reference signs used in the claims pursuantto Rule 6.2(b) of the Patent Cooperation Treaty (“PCT”) do not limit thescope

What is claimed is:
 1. A computer-implemented method, comprising:acquiring one or more initial vital signs from each of a plurality ofpatients; determining a patient acuity measure associated with each ofthe plurality of patients based on the acquired one or more initialvital signs from each of the plurality of patients; establishing, by oneor more processors, a patient monitoring queue that includes theplurality of patients, the plurality of patients being located in anarea that can be captured by one or more vital sign acquisition cameras;unobtrusively acquiring, by one or more of the vital sign acquisitioncameras, one or more updated vital signs from a given patient selectedfrom the patient monitoring queue; determining, by one or more of theprocessors, an updated patient acuity measure for the given patientbased on the one or more updated vital signs unobtrusively acquired bythe one or more vital sign acquisition camera from the given patientusing a machine learning model, detecting, by one or more of theprocessors, based on a comparison of the updated patient acuity measurefor the given patient and the previously determined patient acuitymeasure for the given patient, deterioration of the given patient;updating, by one or more of the processors, the machine learning modelby writing new trained weights for at least one module of the machinelearning model; and providing, by one or more of the processors, outputalerting medical personnel of the deterioration of the given patient,wherein the one or more vital signs cameras acquire the one or moreupdated vital signs by applying image detection algorithms, and whereinthe one or more updated vital signs comprise one or more of bloodpressure, pulse, glucose level, SO₂, photoplethysmogram, respirationrate, temperature, skin color, blood pressure, posture, or sweat levels.2. The computer-implemented method of claim 1, wherein the patientmonitoring queue is ranked based at least in part on the patient acuitymeasures.
 3. The computer-implemented method of claim 2, wherein the oneor more initial vital signs acquired from each patient are acquired withmedical equipment that is different than the one or more vital signacquisition cameras.
 4. The computer-implemented method of claim 2,wherein the given patient is selected from the patient monitoring queuebased on a position of the given patient in the patient monitoringqueue.
 5. The computer-implemented method of claim 4, further comprisingaltering, by one or more of the processors, a position of the givenpatient in the patient monitoring queue based at least in part on theupdated patient acuity measure.
 6. The computer-implemented method ofclaim 1, further comprising identifying, by one or more of theprocessors, the given patient among the plurality of patients in thearea based on a reference image depicting the given patient.
 7. Thecomputer-implemented method of claim 1, wherein the area comprises amedical waiting room.
 8. The computer-implemented method of claim 1,wherein the one or more vital sign acquisition cameras includes apan-tilt-zoom (“PTZ”) camera.
 9. A system comprising: one or moreprocessors; one or more vital sign acquisition cameras operably coupledwith the one or more processors; and memory operably coupled with theone or more processors, wherein the memory stores instructions that, inresponse to execution of the instructions by one or more processors,cause the one or more processors to: acquire one or more initial vitalsigns from each of a plurality of patients; determine a patient acuitymeasure associated with each of the plurality of patients based on theacquired one or more vital signs from each of the plurality of patients;establish a patient monitoring queue that includes the plurality ofpatients, the plurality of patients being located an area that can becaptured by the one or more vital sign acquisition cameras;unobtrusively acquire, by one or more of the vital sign acquisitioncameras, one or more updated vital signs from a given patient selectedfrom the patient monitoring queue; determine an updated patient acuitymeasure for the given patient based on the one or more updated vitalsigns unobtrusively acquired by the one or more vital sign acquisitioncameras from the given patient using a machine learning model; detect,based on a comparison of the updated patient acuity measure for thegiven patient and the previously determined patient acuity measure forthe given patient, deterioration of the given patient; update themachine learning model by writing new trained weights for a least onemodule of the machine learning model; and provide output alertingmedical personnel of the deterioration of the given patient, wherein theone or more vital signs cameras acquire the one or more updated vitalsigns by applying image detection algorithms, and wherein the one ormore updated vital signs comprise one or more of blood pressure, pulse,glucose level, SO₂, photoplethysmogram, respiration rate, temperature,skin color, blood pressure, posture, or sweat levels.
 10. The system ofclaim 9, wherein the plurality of patients are ranked in the patientmonitoring queue based at least in part on the patient acuity measures.11. The system of claim 9, wherein the given patient is selected fromthe patient monitoring queue based on a position of the given patient inthe patient monitoring queue.
 12. The system of claim 9, wherein theoutput comprises one or both of a reference image of the given patientand a location of the given patient in the area.
 13. The system of claim10, further comprising altering, by one or more of the processors, aposition of the given patient in the patient monitoring queue based atleast in part on the updated patient acuity measure.
 14. The system ofclaim 9, further comprising identifying, by one or more of theprocessors, the given patient among the plurality of patients in thearea based on a reference image depicting the given patient.
 15. Atleast one non-transitory computer-readable medium comprisinginstructions that, in response to execution of the instructions by oneor more processors, cause the one or more processors to perform thefollowing operations: acquiring one or more initial vital signs fromeach of a plurality of patients; determining a patient acuity measureassociated with each of the plurality of patients based on the acquiredone or more initial vital signs from each of the plurality of patients;establishing a patient monitoring queue that includes the plurality ofpatients, the plurality of patient being located in an area that can becaptured by one or more vital sign acquisition cameras; unobtrusivelyacquiring, by one or more of the vital sign acquisition cameras, one ormore updated vital signs from a given patient selected from the patientmonitoring queue; determining an updated patient acuity measure for thegiven patient based on the one or more updated vital signs unobtrusivelyacquired by the one or more vital sign acquisition cameras from thegiven patient using a machine learning model; detecting, based on acomparison of the updated patient acuity measure for the given patientand the previously determined patient acuity measure for the givenpatient, deterioration of the given patient; updating the machinelearning model by writing new trained weights for at least one module ofthe machine learning model; and providing output alerting medicalpersonnel of the deterioration of the given patient, wherein the one ormore vital signs cameras acquire the one or more updated vital signs byapplying image detection algorithms, and wherein the one or more updatedvital signs comprise one or more of blood pressure, pulse, glucoselevel, SO₂, photoplethysmogram, respiration rate, temperature, skincolor, blood pressure, posture, or sweat levels.